深度实测AI版支付宝：能卖萌会理财 但还是没法帮我偷别人能量

This article presents an in-depth hands-on test of the AI-powered Alipay during its internal invite-only testing phase, with core takeaways and practical experiences summarized as follows:

1. The AI version of Alipay is currently in an invite-only trial. Users who obtain an invitation code can access it by searching "AI Alipay" on the Alipay homepage and entering the code. The only change is a newly added AI assistant entry on the homepage; users can freely switch between the AI version and the classic version, and there are no major UI overhauls.

2. For popular feature testing: Alipay's AI assistant "Abao" cannot automatically collect Ant Forest energy or feed Ant Manor chickens for users—it only provides a direct entry to the feature, and users still need to complete the operations manually. The bill analysis function performs well: it can generate total expenditure statistics and categorized consumption charts, offer money-saving tips, and allow users to ask follow-up questions for detailed consumption breakdowns.

3. The wealth management feature can deliver basic asset diagnosis and optimization recommendations, with conservative fund recommendations that meet the basic needs of general users, but it does not support direct account custody operations. The experience for daily life services is poor: information is not shared across different features, and users still need multiple redirects and clicks, so there is no notable experience improvement.

This article reveals new trends in big tech's AI布局 (AI deployment) and characteristics of consumer demand through an internal testing experience of AI-powered Alipay, offering key takeaways for brands:

1. In terms of consumer trends: Users' core demand for AI tools is to simplify operations—they want to complete full-process services with a single sentence, and have very high expectations for AI functions that streamline wealth management, consumption and daily life service processes. Brands can match this demand by building AI-powered service functions.

2. In terms of channel opportunities: As a national-level daily life service platform, Alipay hosts more than 4 million mini-programs, with daily life scenarios accounting for 47% of its total usage, making it a core traffic entry for brands targeting offline life services. Alipay's AI upgrade will restructure its traffic distribution logic, and brands can prepare for integration in advance.

3. In terms of risk: Big tech players are taking a generally conservative approach to AI deployment, primarily due to strict security requirements and the need to maintain ecological balance. When accessing the platform's AI ecosystem, brands must prioritize user information security and service compliance to avoid regulatory risks.

This article discloses the latest progress of Alipay's AI initiative, and outlines new opportunities and risk reminders for all types of sellers, summarized as follows:

1. In terms of growth opportunities: Major internet platforms are all accelerating the deployment of AI ecosystems. WeChat has already opened its AI ecosystem to mini-program merchants, and Alipay has launched the AI version for internal testing. AI entries will become a new traffic growth track, and sellers can integrate with the platform's AI ecosystem in advance to capture early traffic dividends.

2. In terms of user demand: Users have a very strong demand for AI to simplify consumption operations, and existing AI functions still suffer from information silos and the need for multiple redirects. Sellers that can collaborate with the platform to optimize service experiences at AI entries will be more likely to win user favor.

3. Risk reminder: AI functions are still in the internal testing stage and most are immature. The platform's overall AI strategy is conservative, so sellers should not invest heavily in AI transformation blindly. It is more prudent to run small-scale tests first, and scale up after functions mature.

This article draws multi-faceted insights for factories advancing digital transformation and expanding e-commerce business based on the development and internal testing experience of AI-powered Alipay:

1. Direction for product and service upgrading: Consumer demand for AI-powered convenient interaction is growing rapidly. When building direct-to-consumer service systems and advancing digital transformation, factories can prioritize AI conversational interaction functions to match users' demand for simpler operations and improve user service experience.

2. In terms of business opportunities: As a national platform with more than 4 million mini-programs and 47% of usage coming from daily life services, Alipay is accelerating the construction of its AI ecosystem and will gradually open AI entries to all industries. Factories doing direct-to-consumer business can connect and布局 (prepare) in advance to secure new traffic channels.

3. Insights for digital advancement: Leading big tech companies have adopted a conservative iterative strategy for AI deployment, prioritizing security and existing ecological balance first. Factories do not need to pursue overnight success when advancing AI and digital transformation; instead, they can iterate step by step, deliver basic functions first and optimize gradually, to avoid unnecessary losses from over-aggressive expansion.

This article reveals current development trends and core pain points of the AI + platform service industry based on hands-on testing of AI-powered Alipay, offering takeaways for service providers:

1. Industry development trends: AI super entries have become a core track competed for by all major internet giants. Alipay, Apple, WeChat, and OpenAI have all accelerated their布局 (deployment) of AI entries recently. Market demand for entry-level AI services is very strong, and the industry has enormous overall growth space.

2. Core pain points for clients: The core pain point for current AI implementation is that most platform functions and ecosystems are independent, with unconnected data forming information silos. AI cannot deeply capture detailed information across functions to achieve end-to-end full-process automation, so it cannot deliver noticeable experience improvements to users.

3. Direction for solutions: Service providers can focus on developing technical solutions for cross-functional data integration and conversational full-process operation implementation, while taking into account data security and compliance requirements, to solve the core pain points of current platform AI upgrades and accurately match market demand.

This article summarizes user demand and lessons from existing deployment based on the internal testing experience of AI-powered Alipay, offering insights for platform companies building their own AI initiatives:

1. Core user demand: Users' core demand for AI platforms is "conversation as service"—they want to complete full-process operations through a single conversation, replacing the original search + multi-layer clicking model to simplify usage. This is the core direction for platforms' AI upgrades.

2. Lessons to adopt: Platforms can learn from Alipay's conservative strategy: prioritize the security of funds and user information first, while balancing the interests of all ecosystem participants on the platform to avoid breaking the existing ecological balance and hurting the platform's overall competitiveness.

3. Pitfalls to avoid: Current AI technology is not yet mature enough to enable full cross-function integration. Platforms should not overhype fully automated or fully managed functions, which would raise user expectations too high and damage reputation. It is better to start with basic functions such as auxiliary analysis and entry provision, then iterate and optimize gradually.

This article discloses the latest industry developments in the battle for AI-era super entries, summarizes the characteristics of current big tech deployment, and offers insights for industry researchers:

1. Latest industry developments: Competition for AI super entries continues to heat up. Recently, Alipay launched an invite-only trial of its AI version, Apple officially announced Siri AI will integrate third-party large models, WeChat opened its AI ecosystem to developers, and OpenAI demonstrated an app-free AI phone. All major tech giants have entered the race to claim AI entry leadership.

2. Common characteristics of current big tech deployment: Leading internet giants are taking a generally conservative approach to AI entry deployment. Alipay AI only adds a new entry on top of the original product, does not overhaul the existing UI, and does not open up automatic operation permissions—it is essentially an incremental upgrade built on the existing ecosystem to balance the multiple demands of security, ecological interests and AI upgrading.

3. In terms of business model: "Conversation as service" is widely recognized as the core business model for future entry-level products, and is expected to replace the existing app distribution model. However, this model is not yet mature, and multiple core issues including data integration, security compliance, and ecological interest balancing still need to be resolved.